What does the expected value of a binomial distribution with n trials tell you?

Mathematics

1 answer:

SVEN [57.7K]4 years ago

3 0

Answer:

The expected value of a binomial distribution with n trials tell us about the the average number of successes

Step-by-step explanation:

A binomial distribution is a frequency distribution of the possible number of successful outcomes in a given number of trials such that there is the same probability of success of each of the outcome.

For n trials with probability of success of each outcome as p, expected value of a binomial distribution is given by $E\left ( X \right )=np$ .

If we toss 200 coins, and X is the number of heads, the expected value of X is 100= (1/2)200.

So, basically the expected value of a binomial distribution with n trials tell us about the the average number of successes .

You might be interested in

What is the unit rate of 5/7 : 4/7?

allochka39001 [22]

9514 1404 393

Answer:

a = 5/4

Step-by-step explanation:

To make the second number in this ratio be 1, you need to multiply the whole ratio by 7/4:

(7/4)(5/7) : (7/4)(4/7) = 5/4 : 1 = a : 1

a = 5/4

6 0

3 years ago

Consider a game in which a participant pays $2 to roll a die. The participant receives $3 if they roll a 1 (i.E. They go up by a

Sauron [17]

Answer:

The expected monetary value of a single roll is $1.17.

Step-by-step explanation:

The sample space of rolling a die is:

S = {1, 2, 3, 4, 5 and 6}

The probability of rolling any of the six numbers is same, i.e.

P (1) = P (2) = P (3) = P (4) = P (5) = P (6) = $\frac{1}{6}$

The expected pay for rolling the numbers are as follows:

E (X = 1) = $3

E (X = 2) = $0

E (X = 3) = $0

E (X = 4) = $0

E (X = 5) = $0

E (X = 6) = $4

The expected value of an experiment is:

$E(X)=\sum x\cdot P(X=x)$

Compute the expected monetary value of a single roll as follows:

$E(X)=\sum x\cdot P(X=x)\\=[E(X=1)\times \frac{1}{6}]+[E(X=2)\times \frac{1}{6}]+[E(X=3)\times \frac{1}{6}]\\+[E(X=4)\times \frac{1}{6}]+[E(X=5)\times \frac{1}{6}]+[E(X=6)\times \frac{1}{6}]\\=[3\times \frac{1}{6}]+[0\times \frac{1}{6}]+[0\times \frac{1}{6}]\\+[0\times \frac{1}{6}]+[0\times \frac{1}{6}]+[4\times \frac{1}{6}]\\=1.17$